Surrogate-assisted Parameter Re-initialization for Differential Evolution

Jing-Yu JI, Man Leung WONG

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Referred Conference Paperpeer-review

2 Citations (Scopus)


With respect to parameter adaptation in meta-heuristic algorithms, a kind of feedback usually exists between parameter adaptation and individuals' survival. It is known that parameters in reproduction operator largely determine the quality of offspring. As feedback, successful survival of individuals can guide the direction in which parameters adapt. However, parameter adaptation only based on the preference of survivors would easily get premature convergence. To alleviate this issue, a parameter re-initialization strategy is proposed to regenerate more reasonable starting points at different stages for parameter adaptation. In this study, support vector regression with radial basis function is used to estimate potential parameter combinations for JADE. The IEEE CEC2014 test suite including 30 benchmark test functions is used to evaluate our proposed strategy. Obtained results are compared with six state-of-the-art optimization algorithms. Statistical analysis demonstrates the effectiveness of the proposed surrogate-assisted parameter re-initialization strategy.

Original languageEnglish
Title of host publicationProceedings of the 2022 IEEE Symposium Series on Computational Intelligence, SSCI 2022
EditorsHisao ISHIBUCHI, Chee-Keong KWOH, Ah-Hwee TAN, Dipti SRINIVASAN, Chunyan MIAO, Anupam TRIVEDI, Keeley CROCKETT
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages8
ISBN (Electronic)9781665487689
Publication statusE-pub ahead of print - 30 Jan 2023
Event2022 IEEE Symposium Series on Computational Intelligence, SSCI 2022 - Singapore, Singapore
Duration: 4 Dec 20227 Dec 2022

Publication series

NameProceedings of the 2022 IEEE Symposium Series on Computational Intelligence, SSCI 2022


Conference2022 IEEE Symposium Series on Computational Intelligence, SSCI 2022

Bibliographical note

Publisher Copyright:
© 2022 IEEE.


  • differential evolution
  • global optimization
  • parameter re-initialization
  • surrogate model


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